KR101628723B1

KR101628723B1 - Method and program for time series image analysis

Info

Publication number: KR101628723B1
Application number: KR1020150041305A
Authority: KR
Inventors: 성유섭; 이덕희; 심우현; 임옥균; 김영은
Original assignee: 재단법인 아산사회복지재단
Priority date: 2015-03-25
Filing date: 2015-03-25
Publication date: 2016-06-09

Abstract

The present invention relates to a time series image analysis method and an analysis program using the same. According to an embodiment of the present invention, a time series image analysis method comprises the steps of: obtaining a first image, e.g., a high-resolution image, and a second image, e.g., a low-resolution image (S100); obtaining time series data for each point in the second image (S200); matching the time series data to each point in the first image corresponding to each point in the second image for which the time series data is obtained (S300); and receiving coordinate data corresponding to a specific point of the first or second image selected by a user, and providing time series data for the selected specific point (S400). The medical team can conduct a diagnosis while confirming a spatial high-resolution image together with time series data at close time intervals, thus reducing a time required for the diagnosis.

Description

METHOD AND PROGRAM FOR TIME SERIES IMAGE ANALYSIS < RTI ID = 0.0 >

The present invention relates to a time-series image analysis method and an analysis program, and more particularly, to a method for performing a time-series thermal analysis easily by using a high-resolution image that is easily spatially observed and a low- will be.

Computed tomography (CT), x-ray imaging, magnetic resonance imaging (MRI), and the like exist as methods for acquiring an internal body image. Computed tomography (CT) is a technique for reconstructing tomographic images of a human body by reconstructing the human projection data obtained by X-ray imaging. An X-ray imaging apparatus generates X-rays and projects the X-rays to a screener, and then converts the light transmitted through the screener to an image using a sensor. Magnetic resonance imaging (MRI) is a method of imaging and reconstructing the magnetic properties of materials constituting the human body. In other words, when MRI is instantaneously fired a radiofrequency that excites a hydrogen nucleus (proton) only after laying a person in a strong magnetic field, the hydrogen nucleus that was excited after a while is relaxed, This is the way the computer calculates this signal to get the image.

It is difficult to diagnose a specific part of a blood vessel or a lesion in an image obtained through various image capturing techniques. Therefore, the contrast enhancement phenomenon occurs by injecting the contrast agent during the image acquisition through various image capturing techniques to perform detailed observation.

In order to observe the blood flow of a specific blood vessel, a time-series analysis using an angiographic image should be performed. An angiographic image acquired at a specific time interval is required for the time-series analysis. If the number of photographed frames is large, a more accurate time-series analysis can be performed. On the other hand, the area to acquire the time-series data can be accurately selected by diagnosing using an angiographic image having high spatial resolution. In order to acquire an angiographic image of a large number of spatially clear frames, there is a problem that the degree of X-ray exposure of the patient becomes large or the photographing time may take a very long time. In addition, there may be a problem that the clear high-resolution image capturing and the image capturing of a large number of frames per unit time can not be performed simultaneously due to the performance limitation of the equipment.

Time series image analysis method and an analysis program for enabling a time series analysis of a medical image to be easily performed by allowing a time series data obtained from a temporally dense low resolution image to be visually checked while checking a high resolution image spatially.

According to an embodiment of the present invention, there is provided a time-series image analysis method comprising: acquiring a first image as a high-resolution image and a second image as a low-resolution image; Obtaining time series data for each point in the second image; Matching the time series data to each point in the first image corresponding to a point in the second image obtained by the time series data; And receiving coordinate data corresponding to a specific point of the first or second image selected by the user and providing time series data of the specific point.

In addition, the image may be a blood flow image acquired through an image acquisition device after injecting a contrast agent that matches a specific image acquisition device.

The time series data may be measured data of a signal enhanced by a time-specific contrast agent measured at a specific time interval of the second image.

Also, the image is a magnetic resonance image, the first image is a structural MRI image photographed at a high resolution through a MRI apparatus, the second image is a low-resolution functional MRI image .

Also, the number of acquired frames of the first image may be smaller than the number of acquired frames of the second image.

The matching step may include synchronizing a frame of the first image and a frame of the second image in correspondence with each other according to a specific criterion.

The method may further include generating a first extracted image or a second extracted image that is a DSA image extracted from the obtained first or second image region.

The method may further include analyzing the time series data to display the contrast point or the maximum contrast point of each of the points.

The time series data providing step may include displaying the first or second image at a specific time point after the contrast agent arrival point for the specific point selected by the user.

Setting the first or second image as a fixed image or a moving image; And determining a position of a moving image that minimizes an error between the fixed image and the moving image.

The method may further include the step of image-processing the first or second image to remove noise.

The time series data matching step may include matching time series data of each pixel in the second image with a plurality of pixels in the first image corresponding to pixels in the second image.

Analyzing the time series data to obtain one of numerical data of an arrival time point or a maximum time point of the contrast agent and generating a color map image in which each pixel is converted into a predetermined color corresponding to the numerical data; .

The time series image analysis program according to another embodiment of the present invention executes the above-mentioned time series image analysis method in combination with hardware and is stored in the medium.

According to the present invention as described above, the following various effects are obtained.

First, the amount of information for analysis can be increased by simultaneously using a high spatial resolution image and a high temporal resolution image. In other words, unlike the conventional method, which does not acquire time series dense time series data by taking a high resolution image, it is possible to confirm the time series dense time data obtained from the low resolution image analysis while observing the high resolution image, There is an effect that can be.

Second, it is possible to precisely check and select a specific point to receive the time series data through the high-resolution image, so that the user can obtain appropriate information on the desired region of interest (ROI).

Third, the medical staff can make a diagnosis by checking the time-series data of the spatially high-resolution image and the dense time interval, and the time required for the diagnosis by the medical staff can be reduced. That is, the medical staff can easily perform the time series analysis of the medical image, thereby reducing the time for the diagnosis result.

Fourthly, in the case of X-ray or CT using radiography, low-resolution images are obtained by using less radiation to acquire dense time series data, thereby reducing the radiation damage that can be caused to the patient.

Fifth, when acquiring an image through MRI, there is an effect of reducing the time required to acquire a plurality of frames. Therefore, it is possible to reduce the time consumed by the patients in order to capture a high-resolution image of a large number of frames, and the hospital can reduce the shooting time, and thus it is possible to carry out the examination of many patients.

Sixth, since the first image or the second image is synchronized, the frame can be changed together with other images according to the frame change of the specific image by the user, so that the medical staff has to adjust the first image and the second image respectively And it is possible to reduce the time required for analysis or diagnosis using an angiographic image.

Seventh, since the arrival time and maximum time point of the clinically necessary contrast agent are automatically detected and provided to the medical staff, it is possible for the medical staff to perform the clinical diagnosis easily.

Eighth, when the positions of the first image and the second image are not matched, matching of the first image and the second image is automatically performed to prevent an error in the process of mapping the time-series data to the first image . Further, even if there is a difference in the position of the patient at the time of photographing the first image and the second image, the correction can be carried out by itself, thereby making it easy to take a medical image.

1 is a flowchart illustrating a time-series image analysis method according to an embodiment of the present invention.
2 is an exemplary diagram of a first image acquired in accordance with an embodiment of the present invention.
FIG. 3A is an exemplary view of a second image obtained before incorporating the contrast agent obtained according to an embodiment of the present invention. FIG.
FIG. 3B is an illustration of a second image when the contrast agent acquired in accordance with an embodiment of the present invention passes through an artery. FIG.
3C is an exemplary illustration of a second image when the contrast agent acquired in accordance with one embodiment of the present invention passes through a vein.
4 is an exemplary view of a first image acquired by an MR device according to an embodiment of the present invention.
5 is an exemplary diagram of a second image acquired by an MR device according to an embodiment of the present invention.
6 is an exemplary diagram for matching time series data to each pixel of a first image according to an embodiment of the present invention.
7 is an exemplary diagram of a time series data graph according to an embodiment of the present invention.
8 is an exemplary diagram of a DSA image according to an embodiment of the present invention.
FIG. 9 is an exemplary diagram for obtaining contrast agent maximum point numerical data for each pixel for color map generation in accordance with an embodiment of the present invention.
10 is an exemplary diagram for generating a color map by converting numeric data for each pixel into a corresponding color according to an embodiment of the present invention.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS The advantages and features of the present invention and the manner of achieving them will become apparent with reference to the embodiments described in detail below with reference to the accompanying drawings. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. To fully disclose the scope of the invention to those skilled in the art, and the invention is only defined by the scope of the claims. Like reference numerals refer to like elements throughout the specification.

Unless defined otherwise, all terms (including technical and scientific terms) used herein may be used in a sense commonly understood by one of ordinary skill in the art to which this invention belongs. Also, commonly used predefined terms are not ideally or excessively interpreted unless explicitly defined otherwise.

The terminology used herein is for the purpose of illustrating embodiments and is not intended to be limiting of the present invention. In the present specification, the singular form includes plural forms unless otherwise specified in the specification. The terms " comprises "and / or" comprising "used in the specification do not exclude the presence or addition of one or more other elements in addition to the stated element.

In the present specification, an angiographic image means an image or an image obtained in the course of performing an angiographic examination. Angiography is a type of test that acquires images of blood vessels by injecting a contrast agent and using an image capturing method using the image measuring device. The imaging method may include X-ray imaging, computed tomography (CT) as well as Magnetic Resonance Imaging (MRI) imaging. The angiographic images include not only the images obtained by the image measuring device after injecting the contrast agent to perform the angiographic examination but also the images obtained before injecting the contrast agent.

In this specification, the computer includes all of various devices capable of performing computational processing to visually present results to a user. For example, the computer may be a smart phone, a tablet PC, a cellular phone, a personal communication service phone (PCS phone), a synchronous / asynchronous A mobile terminal of IMT-2000 (International Mobile Telecommunication-2000), a Palm Personal Computer (PC), a personal digital assistant (PDA), and the like. The computer may also be a medical device that acquires or observes an angiographic image.

1 is a flowchart illustrating a time-series image analysis method according to an embodiment of the present invention. 2 is an exemplary diagram of a first image acquired in accordance with an embodiment of the present invention. 3 is an exemplary diagram of a second image acquired in accordance with an embodiment of the present invention. 4 is an exemplary view of a first image acquired by an MR device according to an embodiment of the present invention. 5 is an exemplary diagram of a second image acquired by an MR device according to an embodiment of the present invention. 6 is an exemplary diagram for matching time series data to each pixel of a first image according to an embodiment of the present invention. 7 is an exemplary diagram of a time series data graph according to an embodiment of the present invention. 8 is an exemplary diagram of a DSA image according to an embodiment of the present invention. FIG. 9 is an exemplary diagram for obtaining contrast medium maximum-point numerical data for each pixel for color map generation according to an embodiment of the present invention. 10 is an exemplary diagram for generating a color map by converting numeric data for each pixel into a corresponding color according to an embodiment of the present invention.

1 to 10 show a frame 100 of a first image; A frame 200 of a second image; Time series data 300 obtained from the second image; Contrast agent arrival time mark 310; And a frame 400 of DSA images.

Hereinafter, a time-series image analysis method and an analysis program according to embodiments of the present invention will be described with reference to the drawings.

1 is a flowchart illustrating a time-series image analysis method according to an embodiment of the present invention.

Referring to FIG. 1, a time-series image analysis method according to an exemplary embodiment of the present invention includes acquiring a first image 100, which is a high-resolution image, and a second image 200, which is a low- resolution image; Acquiring time series data (300) for each point in the second image (200) (S200); (S300) matching the time series data (300) to each point in the first image (100) corresponding to a point in the second image (200) obtained the time series data (300); And receiving coordinate data corresponding to a specific point of the first or second image 200 selected by the user and providing the time series data 300 of the specific point (S400). A time-series image analysis method according to an embodiment of the present invention will be described in order.

The first image 100, which is a high-resolution image, and the second image 200, which is a low-resolution image, are acquired (S100). As shown in FIG. 2, a high-resolution image (first image 100) is composed of many pixels and is spatially clear, meaning an image in which an intra-vessel location can be accurately grasped. As shown in FIG. 3, a low-resolution image (second image 200) has a relatively low resolution (i.e., a small number of pixels forming an image per frame) as compared with a high-resolution image. The computer can directly acquire the first image 100 and the second image 200 from the image capturing apparatus and acquire the first image 200 and the second image 200 already captured by the image capturing apparatus, It can be stored on an external server and recalled when performing analysis.

The first image 100 and the second image 200 may be composed of one or more frames obtained by photographing a specific body part at a specific time interval. The number of acquired frames of the first image 100 may be less than the number of acquired frames of the second image 200. For example, when a high-resolution image is used only for selecting an intra-vascular location to be provided with the time-series data 300, the computer acquires a high-resolution image (first image 100) having a single frame number, (Second image 200) including the frame of the second image 200. [ The computer sets the frame number ratios of the first image 100 and the second image 200 from the user so that the first image 100 and the second image 200, each of which has captured a plurality of frames at specific time intervals, Can be obtained.

In addition, the computer may acquire the first image 100 instead of the second image 200 at a specific time while acquiring the frame of the second image 200 at a short time interval. Thus, the time for the computer to acquire the first image 100 and the second image 200 can be shortened.

A medical image such as a high-resolution image or a low-resolution image may be a blood flow image acquired by using a medical image acquisition device after injecting a contrast agent conforming to a medical image acquisition device such as CT, X-ray, or MRI. When capturing an image using a device using radiation such as CT and X-ray, an angiographic image (i.e., the first image 100 and the second image 200) having different resolutions may be obtained through adjustment of the radiation dose . That is, the computer can acquire a high-resolution angiogram (first image 100) by increasing the amount of radiation (X-ray), and a low-resolution angiogram (second image 200) Can be obtained. At this time, if the radiation dose is increased to acquire a high-resolution angiographic image in a short time interval, the dose of radiation of the patient may be increased and the patient's normal cells may be damaged.

When imaging a contrast image using an MR device, the computer can acquire a spatially high-resolution image (first image 100) such as a T1-weighted image, and can acquire an echo planar image (EPI), a dynamic contrast enhanced (Dynamic image enhancement) images), but a large number of frames (second image 200) can be acquired. In addition, high resolution images and low resolution images can be obtained by the difference in the number of pixels included per frame even in the same imaging method using the MR apparatus. Since the MR device does not utilize the radiation, there is no problem of overexposure during high-resolution imaging, but it takes much time to shoot. That is, the MR imaging takes a very long time to acquire an image having a high spatial resolution and a high temporal resolution (i.e., a tight time interval) in proportion to the number of frames and the number of pixels in the frame. Therefore, Resolution high-resolution contrast image as shown in FIG. 4 and a low-resolution contrast image as shown in FIG. 5, respectively, and then performing synchronization.

In addition, a medical image such as a high-resolution image or a low-resolution image may be an MR image in which the image is photographed in a different manner and has a resolution difference. For example, Functional MRI (MR imaging), which takes images of brain functions, has a very short resolution time per frame. Therefore, it is difficult to accurately determine the structure or position of a body part such as the brain by functional MR imaging only. Therefore, it is possible to acquire a high-resolution structural MR image having high spatial discrimination power and perform time-series analysis in synchronization with low-resolution functional MR images of a plurality of frames.

The computer analyzes the frames of the second image 200 in order of time to acquire time series data 300 for each point (S200). The time series data 300 refers to numerical data on changes in color, brightness, etc. recognized by analyzing pixels corresponding to respective points in a frame of the second image.

For example, when the image is a blood flow image (i.e., an angiogram image) taken by scanning the contrast agent, the time series data may include time-series data measured through a second image 200 frame obtained at specific time intervals And may be measured data of a signal enhanced by the contrast agent. An angiographic image includes a two-dimensional image in which a specific region is enhanced by contrast agent for each frame. That is, before the contrast agent is injected, as shown in FIG. 3A, there is no contrast enhanced blood vessel area. When the contrast agent is injected into the artery, the artery area becomes bright as shown in FIG. 3B, The vein area becomes bright as shown in FIG. 3C. The computer extracts a brightness value corresponding to a specific point (i.e., a specific coordinate) selected by the user in each frame. The computer may generate the extracted brightness values as time series data according to the time order in which each frame is acquired. For example, when the total number of frames of the angiographic image is n, the brightness values generated by generating the matrix of 1 * N can be sequentially input into the matrix. The computer may perform a time series analysis such as plotting a graph based on the matrix data.

The computer matches the time series data 300 to each point in the first image 100 corresponding to the point in the second image 200 obtained the time series data 300 in operation S300. The computer grasps the point of the first image 100 corresponding to the position in the blood vessel that is the same as the point in the second image 200 obtained by obtaining the time series data 300, (300). That is, the computer performs matching between the spatial coordinates of the first image 100 and the second image 200 corresponding to the same point in time.

6, the computer may convert the time series data 300 of each pixel in the second image 200 into a plurality of images in the first image 100 corresponding to the pixels in the second image 200. For example, Pixel. &Lt; / RTI > That is, the computer can match the time series data 300 obtained in the second image 200 pixels to the pixels of the plurality of first images 100 included in one pixel of the second image 200 having a low resolution have. However, the method of matching the time series data 300 obtained from the second image 200 to the first image 100 is not limited to this, and the method of matching the first image 100 and the second image 200 Various methods for applying the same time series data 300 can be applied.

And receives the coordinate data corresponding to the specific point of the first or second image 200 selected by the user and provides the time series data 300 of the specific point at step S400. The computer receives specific point coordinate data of the first or second image 200 from a user such as a medical staff. For example, when a computer uses an input means such as a mouse, when a user places a mouse cursor over a specific point (mouseover), the computer judges the point at which the cursor is located as the selected point, Can be obtained. In addition, when the computer is a device having a touch screen, when the user touches a specific point of the first or second image 200 on the screen from the user, the computer determines the touched specific point as the selection point, Coordinates can be obtained.

Then, the computer provides time series data 300 corresponding to the selected coordinate data. For example, the computer may display time series data 300 corresponding to a particular pixel in the first or second image 200 selected by the user. The computer may provide the time series data 300 in a tabular or graphical form. For example, as shown in FIG. 7, when CT or X-ray imaging is performed, the computer displays X-ray absorption rate or transmittance with respect to the time at which each frame of the second image 200 is acquired, It can be provided in graph form.

Since the same time series data 300 is matched to the same point of the first image 100 and the second image 200, the computer can obtain a specific point in any one of the first or second images 200 from the user The same time-series data 300 can be provided.

In addition, the computer may analyze the time series data 300 to recognize the arrival time point or the maximum time point of the contrast agent at each point. For example, as shown in FIG. 7, the computer can display a time point when the contrast obtained by analyzing the time series data 300 of a specific point arrives on a graph using a specific marker 310 such as a vertical line. The time point at which the contrast agent arrives or the maximum time point can be used to compare the blood flow before and after the treatment to treat anomalous vessels of the artery or vein. The medical staff can utilize the recognition of the arrival time or the maximum time of the contrast agent as an index for judging how well the particular lesion is treated.

The step of providing the time series data 300 may include displaying the first or second image 200 at a specific time point after the contrast agent arrival point for a specific point selected by the user . As shown in FIGS. 3A to 3C, the portion of the blood vessel to be emphasized by contrast enhancement varies depending on the position of the blood vessel passing through the artery after injecting the contrast agent. In order for the medical staff to visually grasp the condition of the blood vessels at the time of the blood vessel inspection, it is necessary for the computer to transmit a frame of the first or the second image 200, which can be clearly recognized by passing a large amount of contrast agent through a specific point selected from the user I need to display it on the screen. Accordingly, the computer can extract and display a frame whose amount of contrast agent passing through a specific point selected based on the time-series data 300 is higher than a specific reference.

The method may further include generating a first extracted image or a second extracted image that is a DSA image 400 extracted from the acquired blood vessel region in the obtained first or second image 200. That is, the computer can extract only the highlighted blood vessel area as the contrast agent passes through, so that only the blood vessel, which is the area of interest of the user, can be closely observed. For this purpose, the computer can generate an image extracting only the blood vessel region except the skeleton which is unnecessary for the clinical diagnosis by excluding the image before contrast agent injection from the image after injecting the contrast agent. The image extracted only from the blood vessel region is referred to as DSA (Digital Subtraction Angiography) image. By utilizing the DSA image 400, a medical practitioner can accurately select a point at which the time series data 300 is to be confirmed, and the blood flow at a specific point (for example, whether the blood flows out of the normal state or not Etc.) can be accurately observed.

The matching step S300 may include synchronizing a frame of the first image 100 with a frame of the second image 200 according to a specific criterion. The specific criterion corresponds to a matching rule between the frame of the first image 100 and the frame of the second image 200, the number of which is different.

For example, when a time interval between acquiring a plurality of frames of the first image 100 and a time interval obtained by acquiring a plurality of frames of the second image 200 correspond to a multiple relation, The frame of the second image 200 corresponding to each frame of the first image 200 may be determined and the frame of the first or second image 200 may be synchronized. In addition, the computer can set a frame of the first image 100 to which each frame of the second image 200 is to be associated. That is, since the number of frames of the first image 100 is smaller than the number of frames of the second image 200, the computer determines the range of the second image 200 to correspond to each frame of the first image 100, . In one embodiment, when the consecutive frames in the first image are the first frame and the second frame, the computer can set the reference time point as an intermediate point of time when the first frame and the second frame are respectively acquired. Thereafter, the computer obtains a frame obtained before the reference time point among the second image frames captured between the acquisition time points of the first frame and the second frame, matches the first frame, . &Lt; / RTI > The specific reference or method for the computer to match a plurality of frames of the second image 200 to the frame of the first image 100 is not limited to this, And a method of performing matching on the basis of the number of frames of the second image 200 corresponding to a specific frame of the image 100 may be applied.

Accordingly, when the medical staff selects a specific frame of the first image 100 or the second image 200, when a proper frame of another image (for example, when a specific frame of the first image 100 is selected) A frame of the second image 200 corresponding to a time when a specific frame of the first image 100 is acquired). In addition, when automatically providing an optimal frame of a specific point selected by the user (for example, a frame in which the amount of passage of the contrast agent is large and the blood vessel can be easily observed), the medical staff automatically selects a particular one of the first or second images 200 The optimal frame of the first image 100 and the second image 200 may be provided together. Therefore, the medical staff can solve the inconvenience of adjusting the first image 100 and the second image 200, respectively, and it is possible to reduce the time required for analysis or diagnosis using the angiographic image.

Setting the first or second image 200 as a fixed image or a moving image; And determining a position of a moving image that minimizes an error between the fixed image and the moving image. The location of the specific region of the first image 100 and the second region 200 captured by the patient may be the same because of the small motion of the patient but the movement is caused by various causes (for example, respiration, etc.) The positions of the specific points of the first image 100 and the second image 200 may not coincide with each other. When the first image 100 and the second image 200 are not obtained at the same time so that the photographing positions are different or the patient moves during the photographing, the positions of the specific points in the first image 100 and the second image 200 May not coincide with each other. Therefore, in this case, the computer needs to perform a process of matching the first image 100 with the second image 200. [

Accordingly, the computer sets the first image 100 or the second image 200 as a fixed image or a moving image, and determines whether the fixed image and the moving image are properly matched (i.e., determines whether the position of the moving image is appropriate) The moving image can be moved to the optimized position by judging the appropriateness of the position of the moving image through various matching methods. The fixed image means an image fixed at a specific position to be a reference of image matching. The moving image means an image moving to a suitable position with respect to a fixed image for image matching. As a method for determining the degree of matching between a fixed image and a moving image, a computer may calculate the error using a sum of absolute values or square values of the difference in signal intensity at the same point in a fixed image and a moving image, a correlation coefficient, A method of measuring similarity measure such as mutual information amount can be applied. After that, the computer can move the position of the moving image based on the calculated matching degree. The computer can determine the matching degree and move the position of the moving image several times for accurate image matching. This makes it possible to prevent an error in the process of matching the time series data 300 to the first image 100 by matching the first image 100 and the second image 200.

The method may further include image processing the first or second image 200 to remove noise. The computer may remove noise included in the first or second image 200 in order to accurately grasp the amount of the contrast agent or observe the blood vessel accurately in the first image 100 or the second image 200 There is a need. The computer can perform spatial smoothing or temporal smoothing with a noise canceling method.

Spatial smoothing refers to a method of correcting noise or errors occurring in a specific frame of the first or second image 200. [ The computer may perform spatial smoothing of each frame of the first or second image 200 using a filter such as a mean filter or a Gaussian filter. The computer may receive the intensity of the smoothing from the user, and may determine the appropriate smoothing intensity through its own calculation. In addition, the computer may compare the numerical values of the pixels of the first image 100 and the second image 200 in the spatial smoothing process, and perform correction to an appropriate value. Temporal smoothing refers to the correction of the time series data 300 of a specific pixel obtained through the analysis of the second image 200. The computer may perform temporal smoothing using a moving average method or a method of excluding data corresponding to an outlier among the time series data 300. [ This allows correction (noise cancellation) of non-ideal data (e.g., non-ideally discontinuous temporal data on a continuous blood flow, or non-idealally different pixels compared to adjacent regions in space) 300) can be increased.

According to an embodiment of the present invention, the time-series data is analyzed to acquire numerical data of any one of an arrival time point and a maximum time point of the contrast agent, and a color map in which each pixel is converted into a predetermined color corresponding to the numeric data And generating an image based on the image data. First, the computer may analyze the time series data to obtain numerical data such as an arrival time and a maximum time point of the contrast agent. Thereafter, the computer can generate a color map image in which each pixel is converted to a predetermined color corresponding to the numerical data. For example, as shown in FIG. 9, the computer can extract numeric data corresponding to each pixel necessary for generating a color map relating to a specific analysis result. If the user wishes to generate a color map for the maximum point in time of the contrast agent, the computer may obtain maximum point value data of the contrast agent corresponding to each pixel. Then, as shown in FIG. 10, the computer can recognize a color corresponding to the obtained numerical data according to a correspondence relationship between a predetermined color and a numerical value, and apply the recognized color to each pixel to generate a color map have.

As described above, the time-series image analysis method according to an embodiment of the present invention can be implemented as a program (or application) to be executed in combination with a hardware computer and stored in a medium.

The above-described program may be stored in a computer-readable medium such as C, C ++, JAVA, machine language, or the like that can be read by the processor (CPU) of the computer through the device interface of the computer, And may include a code encoded in a computer language of the computer. Such code may include a functional code related to a function or the like that defines necessary functions for executing the above methods, and includes a control code related to an execution procedure necessary for the processor of the computer to execute the functions in a predetermined procedure can do. Further, such code may further include memory reference related code as to whether the additional information or media needed to cause the processor of the computer to execute the functions should be referred to at any location (address) of the internal or external memory of the computer have. Also, when the processor of the computer needs to communicate with any other computer or server that is remote to execute the functions, the code may be communicated to any other computer or server remotely using the communication module of the computer A communication-related code for determining whether to communicate, what information or media should be transmitted or received during communication, and the like.

The medium to be stored is not a medium for storing data for a short time such as a register, a cache, a memory, etc., but means a medium that semi-permanently stores data and is capable of being read by a device. Specifically, examples of the medium to be stored include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage, and the like, but are not limited thereto. That is, the program may be stored in various recording media on various servers to which the computer can access, or on various recording media on the user's computer. In addition, the medium may be distributed to a network-connected computer system so that computer-readable codes may be stored in a distributed manner.

Eighth, when the positions of the first image and the second image are not matched, matching of the first image and the second image is automatically performed to prevent an error in the process of mapping the time-series data to the first image . Further, even if there is a difference in the position of the patient when photographing the first image and the second image, the correction can be performed by itself, which makes it easy to take an angiographic image.

While the present invention has been described in connection with what is presently considered to be practical exemplary embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, You will understand. It is therefore to be understood that the above-described embodiments are illustrative in all aspects and not restrictive.

100: frame of the first image 200: frame of the second image
300: time series data obtained from the second image
310: Signs on the arrival of contrast media
400: frame of DSA image

Claims

Obtaining a first image as a high-resolution image and a second image as a low-resolution image;
Obtaining time series data for each point in the second image;
Matching the time series data to each point in the first image corresponding to a point in the second image obtained by the time series data; And
And receiving coordinate data corresponding to a specific point of the first or second image selected by the user and providing time series data of the specific point.

The method according to claim 1,
Wherein the image includes:
Wherein the blood flow image acquired by the image acquisition device after injecting a contrast agent corresponding to a specific image acquisition device is obtained.

3. The method of claim 2,
The time-
Wherein the measurement data of the signal enhanced by the time-specific contrast agent of each of the specific points measured through the frame obtained at a specific time interval of the second image.

The method according to claim 1,
Wherein the image is a magnetic resonance image,
Wherein the first image is a structural MRI image photographed at a high resolution through a MRI apparatus,
And the second image is a low-resolution functional magnetic resonance image obtained by obtaining a plurality of frames in a time series.

5. The method according to any one of claims 1 to 4,
Wherein the number of acquired frames of the first image is less than the number of acquired frames of the second image.

5. The method according to any one of claims 1 to 4,
The matching step comprises:
And synchronizing the frame of the first image and the frame of the second image in correspondence with each other according to a specific criterion.

4. The method according to any one of claims 1 to 3,
And generating a first extracted image or a second extracted image that is a DSA image extracted from the obtained first or second image region.

4. The method according to any one of claims 1 to 3,
And analyzing the time series data to display a contrast agent arrival point or a maximum point of time at each of the points.

9. The method of claim 8,
The time-series data providing step may include:
And displaying a first or second image at a specific time point after the contrast agent arrival point for the specific point selected by the user.

5. The method according to any one of claims 1 to 4,
Setting the first or second image as a fixed image or a moving image; And
And determining a position of the moving image that minimizes an error between the fixed image and the moving image.

5. The method according to any one of claims 1 to 4,
And removing noise by image processing the first or second image.

5. The method according to any one of claims 1 to 4,
Wherein the time series data matching step comprises:
Wherein the time series data of each pixel in the second image is matched to a plurality of pixels in the first image corresponding to the pixels in the second image.

5. The method according to any one of claims 1 to 4,
Analyzing the time series data to obtain numerical data of any one of an arrival time point and a maximum time point of the contrast agent and generating a color map image in which each pixel is converted into a predetermined color corresponding to the numerical data; , Time series image analysis method.

A computer-readable recording medium having recorded thereon a time-series image analysis program for causing a client that is a hardware to execute the method according to any one of claims 1 to 4.